Algorithmic Culture
Ted Striphas, “Algorithmic Culture” European Journal of Cultural Studies (2015) Context • Alexander Galloway describes “Algorithmic culture” as the ways computers and algorithms now help define how we think and interact with objects, texts and other people. • Algorithmic Culture has been praised as being completely revolutionary and “new” and also as being objective and egalitarian. • Part of a larger themed journal volume on “big data, data mining and analytics” Main Argument Algorithmic Culture has led to a “reshuffling of some of the words most closely associated with culture, giving rise to new senses of the term that may be experientially available but have yet to be well named, documented, or recorded.” (395) ** What does he mean by reshuffling?** The Stakes of the argument: “these changes have led to the gradual abandonment of culture’s publicness and the emergence of a strange new breed of elite culture purporting to be its opposite.” (395) **Is this really true? Sub Arguments • Algorithmic culture may in some ways be new, but it has a long history, and it is neither objective nor egalitarian. • Culture has always, on some level, been authoritative, and interested in driving out anarchy. • The secrecy/cyphering of Algorithmic Culture is similar to Matthew Arnold’s apostolic vision for culture (It is not egalitarian). Structure and Method • “Historico-definitional” • Based on Raymond William’s Keywords. • Catachresisà how can lexical misuse help reveal the cultural meanings/transformations in the term itself? • KEYWORDS TODAY: How was Keywords a product of its time and how would it be different if written today? • INFORMATION: Striphas sketches this term from “intrinsic quality” to “extrinsic sense data” and how this move was supposed to be equitable (but may not have ended up that way). • CROWD: The meaning of this term started as largely pejorative but has recently developed positive connotations. Like information, it has also become more immaterial/abstract lately to refer more to the commons or a community. •ALGORITHM: It came from an Arabic word with two opposing meanings: arithmetic (which exposes meaning and truth) and cypher (a coding system meant to conceal) **Do algorithms hide more than they reveal? •CONCLUSION: These changing terms suggest ways in which culture is now a more secretive, mystical process in line with a heightened (rather than more equitable) type of cultural experience. Evidence -> largely anecdotal and discursive. •#AmazonFail—example of how “the delegation of the work of culture” to computers can have real, noticeable effects. Culture is now subject to machine-based information processing. **is this really an algorithmic issue? • Focus on how a wide variety of scholars (with a focus on information and digital scholars) and “technologists” have employed these terms. They are, as he states, Old White Men. • Striphas reserves discussion of actual “algorithmic” things to the intro and conclusion. **How would Striphas’ definitions be different if he relied on popular uses of these terms rather than scholarly uses? Notable/Brilliant Moments On Information: “No longer would human beings hold exclusive rights as cultural producers, arbiters, curators or interpreters – a welcome development, perhaps, given the shame, disrespect and brutality elites have long exacted in the name of cultural difference. But what if the apparent uniformity between people and machines resulted in cultural practices and decision-making that were no better informed?” Conclusion: All this makes algorithmic culture sound as if it were the ultimate achievement of democratic public culture. Now anyone with an Internet connection gets to have a role in determining ‘the best that has been thought and said’! I am tempted to follow here by saying, ‘much to the chagrin of Matthew Arnold’, but I am not convinced that algorithmic culture is all that far removed – in spirit, if not execution – from a kind of Arnoldian project. Despite the populist rhetoric, I believe we are returning to something like his apostolic vision for culture. Yet, it seems to me that ‘crowd wisdom’ is largely just a stand-in – a placeholder, an algorism ''– for algorithmic data processing, which is increasingly becoming a private, exclusive and indeed profitable affair. This is why, in our time, I believe that ''algorithms ''are becoming decisive, and why companies like Amazon, Google and Facebook are fast becoming, despite their populist rhetoric, the new apostles of culture. Questions? Striphas suggests that ''Keywords is premised on culture being defined by human interactions but that this may not now be true. How would such a change affect the usefulness of Keywords?